词汇分散情节是天生的 [英] Lexical dispersion plot is seaborn

问题描述

我正在使用seaborn模块生成类似于以下示例的图。

 将熊猫导入为pd 
导入matplotlib.pyplot as plt 
导入numpy as np 
导入seaborn as sns 
 location = /global/scratch/umalmonj/WRF/juris/golden_hourly_manual_obs.csv 
 
 df = pd.read_csv（location，usecols = [ Year， Month， Day， Time， Weather]，parse_dates = [[ Year， Month， Day ， Time]]）
  

我有一个df，看起来像：

  Year_Month_Day_Time天气
 0 2010-01-01 00:00:00 NaN 
 1 2010-01-01 01:00： 00 NaN 
 2 2010-01-01 02:00:00 NaN 
 .. 
 7 2010-01-01 07:00:00 Snow 
 8 2010-01-01 08:00:00雪
 9 2010-01-01 09:00:00阵雪
 .. 
 18 2010-01-01 18:00:00 NaN 
 19 2010-01-01 19:00:00 NaN 
 20 2010-01-01 20:00:00 NaN 
 ... ... ... 
 2861 2010-04-30 05:00:00主要清除
 2862 2010-04-30 06:00:00主要清除
 2863 2010-04-30 07:00:00大部分多云
  

我想用不同的天气类别创建类似的海上带状图到以下情节。

也称为词汇分散图。

任何

我的csv格式的示例数据集可在此处找到

I am using the seaborn module to produce a plot similar to the example below.

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
location = "/global/scratch/umalmonj/WRF/juris/golden_hourly_manual_obs.csv"

df = pd.read_csv(location,usecols= ["Year","Month","Day","Time","Weather"],parse_dates=[["Year","Month","Day","Time"]])

I have a df that looks like:

     Year_Month_Day_Time        Weather
0    2010-01-01 00:00:00            NaN
1    2010-01-01 01:00:00            NaN
2    2010-01-01 02:00:00            NaN
..    
7    2010-01-01 07:00:00           Snow
8    2010-01-01 08:00:00           Snow
9    2010-01-01 09:00:00   Snow Showers
..
18   2010-01-01 18:00:00            NaN
19   2010-01-01 19:00:00            NaN
20   2010-01-01 20:00:00            NaN
...                  ...            ...
2861 2010-04-30 05:00:00   Mainly Clear
2862 2010-04-30 06:00:00   Mainly Clear
2863 2010-04-30 07:00:00  Mostly Cloudy

I want to create a seaborn stripplot with the different weather categories something similar to the following plot.

Also known as a lexical dispersion plot.

Any help would be great!

My sample dataset in a csv format can be found here https://www.dropbox.com/s/ulzz5x3rsl2yjd5/sample_data.csv?dl=0

解决方案

You have to use stripplot. Firstly, you have to properly read datetime column of your data and then plot it:

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# datetime parser
dateparse = lambda x: pd.datetime.strptime(x, '%y/%m/%d %H:%M')
df = pd.read_csv('./sample_data.csv',parse_dates=['DateTime'], date_parser=dateparse)

# set size of figure
plt.figure(figsize=(22,6))
# use horizontal stripplot with x marker size of 5
sns.stripplot(y='Weather',x='DateTime', data=df,
 orient='h', marker='X', color='navy', size=5)
# rotate x tick labels
plt.xticks(rotation=15)
# remover borders of plot
plt.tight_layout()
plt.show()

Figure is clickable

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